--------------------------------Using matlotlib------------------------------------------
1. PIE CHART
A pie chart helps organize and show data as a percentage of a whole. The table below, can be represented in Pie chart
| FOOD | PERCENTAGE |
|---|---|
| Fruit | 36 |
| Vegetables | 14 |
| Dairy | 13 |
| Protein | 28 |
| Grains | 9 |
from matplotlib import pyplot as plt
labels = 'Fruit', 'Vegetables', 'Dairy', 'Protein','Grains'
sizes = [36, 14, 13, 28, 9]
explode = (0.3, 0, 0, 0, 0) # only "explode" the 1st slice (i.e. 'Fruit')
fig, ax = plt.subplots()
ax.pie(sizes, explode=explode, labels=labels, autopct='%1.1f%%',
shadow=True, startangle=90)
plt.show()
--------------------------------Using seaborn------------------------------------------
2. BAR PLOT
A bar plot shows the relationship between a numeric and a categoric variable.
import seaborn as sns
custom_params = {"axes.spines.right": False, "axes.spines.top": False}
sns.set_theme(style="ticks", rc=custom_params)
sns.barplot(x=["2021", "2022", "2023"], y=[750, 1500, 1145])
<Axes: >
--------------------------------Using plotly------------------------------------------
3. SCATTER PLOT
It is used to observe relationship between variables. It uses dots to represent the relationship between the variables.
import plotly
from plotly import express as px
dataframe = px.data.iris()
fig = px.scatter(dataframe, x="petal_width", y="petal_length",color="species",title="Iris Dataset-Relationship")
fig.show()
plotly.offline.init_notebook_mode()
--------------------------------Using matlotlib------------------------------------------
4. LINE GRAPH
Line graphs are used to track changes over short and long periods of time.
import pandas as pd
import matplotlib.pyplot as plt
placement_data = {'year': [2014, 2015, 2016, 2017, 2018, 2019, 2020, 2021, 2022, 2023],
'employment_rate': [4.5, 5.5, 6.5, 7.0, 7.5, 6.0, 4.5, 5.6, 7.5, 9.5]
}
df = pd.DataFrame(placement_data)
plt.plot(df['year'], df['employment_rate'], color='green', marker='H')
plt.title('PLACEMENT CELL DATA FOR THE LAST 10 YEARS', fontsize=12)
plt.xlabel('year', fontsize=12)
plt.ylabel('employment rate', fontsize=12)
plt.grid(True)
plt.show()
